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IEEE Computational Intelligence Magazine

Issue 3 • Aug. 2017

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Displaying Results 1 - 20 of 20
  • Front Cover

    Publication Year: 2017, Page(s): C1
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  • IEEE WCCI 2018

    Publication Year: 2017, Page(s): C2
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  • Table of Contents

    Publication Year: 2017, Page(s): 1
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  • CIM Editorial Board

    Publication Year: 2017, Page(s): 2
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  • After 30 Years of Work in Osaka [Editor's Remarks]

    Publication Year: 2017, Page(s): 2
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  • SSCI2017

    Publication Year: 2017, Page(s): 3
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  • Ethics and the Social Impact of Computational Intelligence [President's Message]

    Publication Year: 2017, Page(s):4 - 5
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  • CIS Society Officers

    Publication Year: 2017, Page(s): 4
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  • CIS Publication Spotlight [Publication Spotlight]

    Publication Year: 2017, Page(s):6 - 9
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  • Natural Language Generation with Computational Intelligence [Guest Editorial]

    Publication Year: 2017, Page(s):8 - 9
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  • Data-to-Text Generation Improves Decision-Making Under Uncertainty

    Publication Year: 2017, Page(s):10 - 17
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1211 KB)

    Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. This article presents a comparison of different information presentations for uncertain data and, for the first time, measures their effects on human decision-making, in the domain of weather forecast generation. We use a game-based setup to evaluate the different systems. We show th... View full abstract»

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  • Domain Transfer for Deep Natural Language Generation from Abstract Meaning Representations

    Publication Year: 2017, Page(s):18 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2351 KB)

    Stochastic natural language generation systems that are trained from labelled datasets are often domainspecific in their annotation and in their mapping from semantic input representations to lexical-syntactic outputs. As a result, learnt models fail to generalize across domains, heavily restricting their usability beyond single applications. In this article, we focus on the problem of domain adap... View full abstract»

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  • Learning to Generate Descriptions of Visual Data Anchored in Spatial Relations

    Publication Year: 2017, Page(s):29 - 42
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1892 KB)

    The explosive growth of visual data both online and offline in private and public repositories has led to urgent requirements for better ways to index, search, retrieve, process and manage visual content. Automatic methods for generating image descriptions can help with all these tasks, and also play an important role in assistive technology for the visually impaired. The task we address in this p... View full abstract»

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  • Pattern Recommendation in Task-oriented Applications: A Multi-Objective Perspective [Application Notes]

    Publication Year: 2017, Page(s):43 - 53
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1670 KB)

    Task-oriented pattern mining is to find the most popular and complete pattern for task-oriented applications such as goods match recommendation and print area recommendation. In these applications, the measure support is used to capture the popularity of patterns, while the measure occupancy is adopted to capture the completeness of patterns. Existing methods for mining task-oriented patterns usua... View full abstract»

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  • Gene Expression Programming: A Survey [Review Article]

    Publication Year: 2017, Page(s):54 - 72
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  • IEEE Transactions on Emerging Topics in Computational Intelligence

    Publication Year: 2017, Page(s): 73
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  • [Conference Calendar]

    Publication Year: 2017, Page(s):74 - 75
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  • Call for Papers for Journal Special Issues

    Publication Year: 2017, Page(s): 75
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  • CIG 2018

    Publication Year: 2017, Page(s): C3
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  • SSCI2018

    Publication Year: 2017, Page(s): C4
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Aims & Scope

The IEEE Computational Intelligence Magazine (CIM) publishes peer-reviewed articles that present emerging novel discoveries, important insights, or tutorial surveys in all areas of computational intelligence design and applications, in keeping with the Field of Interest of the IEEE Computational Intelligence Society (IEEE/CIS).

Full Aims & Scope